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ORNL engineer Canan Karakaya uses computational modeling to design and improve chemical reactors and how they are operated to convert methane, carbon dioxide, ammonia or ethanol into higher-value chemicals or energy-dense fuels. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Canan Karakaya, a R&D Staff member in the Chemical Process Scale-Up group at ORNL, was inspired to become a chemical engineer after she experienced a magical transformation that turned ammonia gas into ammonium nitrate, turning a liquid into white flakes gently floating through the air. 

Prasad Kandula builds a medium-voltage solid state circuit breaker as part of ORNL’s project to develop medium-voltage power electronics in GRID-C. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Scientists at ORNL are looking for a happy medium to enable the grid of the future, filling a gap between high and low voltages for power electronics technology that underpins the modern U.S. electric grid.

Researchers at Corning have found that understanding the stability of the rings of atoms in glass materials can help predict the performance of glass products.

Corning uses neutron scattering to study the stability of different types of glass. Recently, researchers for the company have found that understanding the stability of the rings of atoms in glass materials can help predict the performance of glass products.

Prasanna Balaprakash, who leads ORNL’s AI Initiative, participated in events hosted by the White House Office of Science and Technology Policy and the Task Force on American Innovation to discuss the challenges and opportunities posed by AI. Credit: Brian Mosley/Computing Research Association

In summer 2023, ORNL's Prasanna Balaprakash was invited to speak at a roundtable discussion focused on the importance of academic artificial intelligence research and development hosted by the White House Office of Science and Technology Policy and the U.S. National Science Foundation.

Alexey Serov researches ways to improve hydrogen fuel cells and materials and the electrolysis process. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

It would be a challenge for any scientist to match Alexey Serov’s rate of inventions related to green hydrogen fuel. But this researcher at ORNL has 84 patents with at least 35 more under review, so his electrifying pace is unlikely to slow down any time soon.

Wire arc additive manufacturing allowed this robot arm at ORNL to transform metal wire into a complete steam turbine blade like those used in power plants. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Researchers at ORNL became the first to 3D-print large rotating steam turbine blades for generating energy in power plants.

Naval Academy midshipmen look at tiny particle fuels while touring ORNL. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy

Nuclear engineering students from the United States Military Academy and United States Naval Academy are working with researchers at ORNL to complete design concepts for a nuclear propulsion rocket to go to space in 2027 as part of the Defense Advanced Research Projects Agency DRACO program.

Frontier’s exascale power enables the Simple Cloud-Resolving E3SM Atmosphere Model to run years’ worth of climate simulations at unprecedented speed and scale. Credit: Ben Hillman/Sandia National Laboratories, U.S. Dept. of Energy

A 19-member team of scientists from across the national laboratory complex won the Association for Computing Machinery’s 2023 Gordon Bell Special Prize for Climate Modeling for developing a model that uses the world’s first exascale supercomputer to simulate decades’ worth of cloud formations.

A Univ. of Michigan-led team used Frontier, the world’s first exascale supercomputer, to simulate a system of nearly 75,000 magnesium atoms at near-quantum accuracy. Credit: SC23

 

A team of eight scientists won the Association for Computing Machinery’s 2023 Gordon Bell Prize for their study that used the world’s first exascale supercomputer to run one of the largest simulations of an alloy ever and achieve near-quantum accuracy.

Sangkeun “Matt” Lee received the Best Poster Award at the Institute of Electrical and Electronics Engineers 24th International Conference on Information Reuse and Integration.

Lee's paper at the August conference in Bellevue, Washington, combined weather and power outage data for three states – Texas, Michigan and Hawaii –  and used a machine learning model to predict how extreme weather such as thunderstorms, floods and tornadoes would affect local power grids and to estimate the risk for outages. The paper relied on data from the National Weather Service and the U.S. Department of Energy’s Environment for Analysis of Geo-Located Energy Information, or EAGLE-I, database.